{ "_id": "6a21b201cd65a98ecbd39f5a", "Package": "dcvar", "Title": "Dynamic Copula VAR Models for Time-Varying Dependence", "Version": "0.3.1", "Authors@R": "person(\"Benedikt\", \"Lugauer\", , \"benedikt.lugauer@uni-leipzig.de\",\nrole = c(\"aut\", \"cre\"))", "Description": "Fits Bayesian copula vector autoregressive models for\nbivariate time series with dynamic, regime-switching, and\nconstant dependence structures. The package includes\nsimulation, data preparation, estimation with 'Stan' through\n'rstan' or 'cmdstanr', posterior summaries, diagnostics,\ntrajectory extraction, fitted and predictive summaries, and\napproximate leave-one-out cross-validation model comparison for\nsupported fits. For Bayesian computation and model comparison,\nsee Carpenter et al. (2017) and\nVehtari, Gelman and Gabry (2017)\n.", "License": "GPL (>= 3)", "URL": "https://github.com/benlug/dcvar", "BugReports": "https://github.com/benlug/dcvar/issues", "Encoding": "UTF-8", "Language": "en-US", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "Additional_repositories": "https://stan-dev.r-universe.dev", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "Config/pak/sysreqs": "make libicu-dev", "Repository": "https://benlug.r-universe.dev", "Date/Publication": "2026-06-04 14:41:35 UTC", "RemoteUrl": "https://github.com/benlug/dcvar", "RemoteRef": "HEAD", "RemoteSha": "28910395dbda7ad7ac94195d2d2efa4fa5e0ee41", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-04 17:03:04 UTC", "User": "root" }, "Author": "Benedikt Lugauer [aut, cre]", "Maintainer": "Benedikt Lugauer ", "MD5sum": "01054ff58ad86034259c3799f51dbcfe", "_user": "benlug", "_type": "src", "_file": "dcvar_0.3.1.tar.gz", "_fileid": "2cec67aed6426a64b452747b49778f179172d141d8f08fbc5ccf7cc63e25003f", "_filesize": 622240, "_sha256": "2cec67aed6426a64b452747b49778f179172d141d8f08fbc5ccf7cc63e25003f", "_created": "2026-06-04T17:03:04.000Z", "_published": "2026-06-04T17:12:33.554Z", "_distro": "noble", "_jobs": [ { "job": 79572077734, "time": 317, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7418007622" }, { "job": 79572077725, "time": 322, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7418009488" }, { "job": 79572077727, "time": 193, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7418089368" }, { "job": 79572077755, "time": 139, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7418075095" }, { "job": 79570954122, "time": 358, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7417885902" }, { "job": 79572077835, "time": 290, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7417997759" }, { "job": 79572077767, "time": 155, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "7417946588" }, { "job": 79572077773, "time": 148, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "7417943991" }, { "job": 79572077810, "time": 165, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "7417950621" } ], "_buildurl": "https://github.com/r-universe/benlug/actions/runs/26966650463", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/benlug/dcvar", "_commit": { "id": "28910395dbda7ad7ac94195d2d2efa4fa5e0ee41", "author": "Benedikt Lugauer ", "committer": "GitHub ", "message": "Merge pull request #2 from benlug/fix/package-cleanup\n\nPackage cleanup: audit fixes + docs alignment (v0.3.1)", "time": 1780584095 }, "_maintainer": { "name": "Benedikt Lugauer", "email": "benedikt.lugauer@uni-leipzig.de" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.1.0", "role": "Depends" }, { "package": "rstan", "version": ">= 2.26.0", "role": "Imports" }, { "package": "posterior", "version": ">= 1.5.0", "role": "Imports" }, { "package": "loo", "version": ">= 2.7.0", "role": "Imports" }, { "package": "ggplot2", "version": ">= 3.4.0", "role": "Imports" }, { "package": "patchwork", "version": ">= 1.1.0", "role": "Imports" }, { "package": "bayesplot", "version": ">= 1.10.0", "role": "Imports" }, { "package": "rlang", "version": ">= 1.0.0", "role": "Imports" }, { "package": "cli", "version": ">= 3.0.0", "role": "Imports" }, { "package": "parallel", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "tools", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "cmdstanr", "version": ">= 0.8.0", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "withr", "role": "Suggests" }, { "package": "sn", "role": "Suggests" } ], "_owner": "benlug", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2026-11", "n": 5 }, { "week": "2026-16", "n": 7 }, { "week": "2026-17", "n": 7 }, { "week": "2026-23", "n": 2 } ], "_tags": [ { "name": "v0.3.0", "date": "2026-06-03" } ], "_stars": 2, "_contributors": [ { "user": "benlug", "count": 56, "uuid": 28674098 } ], "_userbio": { "uuid": 28674098, "type": "user", "name": "Benedikt Lugauer" }, "_downloads": { "count": 474, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/dcvar" }, "_devurl": "https://github.com/benlug/dcvar", "_searchresults": 0, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/dcvar.html", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_homeurl": "https://github.com/benlug/dcvar", "_realowner": "benlug", "_cranurl": true, "_releases": [ { "version": "0.1.0", "date": "2026-04-22" }, { "version": "0.2.0", "date": "2026-04-27" } ], "_exports": [ "aggregate_metrics", "compute_param_metrics", "compute_rho_metrics", "covariate_effects", "dcvar", "dcvar_compare", "dcvar_constant", "dcvar_covariate", "dcvar_diagnostics", "dcvar_hmm", "dcvar_multilevel", "dcvar_sem", "dcvar_stan_path", "dependence_summary", "draws", "hmm_states", "interpret_rho_trajectory", "latent_states", "pit_test", "pit_values", "plot_diagnostics", "plot_hmm_states", "plot_latent_states", "plot_phi", "plot_pit", "plot_ppc", "plot_random_effects", "plot_rho", "plot_trajectories", "prepare_constant_data", "prepare_dcvar_covariate_data", "prepare_dcvar_data", "prepare_hmm_data", "prepare_multilevel_data", "prepare_sem_data", "random_effects", "rho_constant", "rho_decreasing", "rho_double_step", "rho_increasing", "rho_random_walk", "rho_scenario", "rho_step", "rho_trajectory", "simulate_breakpoint_data", "simulate_dcvar", "simulate_dcvar_multilevel", "simulate_dcvar_sem", "var_params" ], "_help": [ { "page": "aggregate_metrics", "title": "Aggregate metrics across simulation replications", "topics": [ "aggregate_metrics" ] }, { "page": "as.data.frame.dcvar_model_fit", "title": "Convert a dcvar fit summary to a data frame", "topics": [ "as.data.frame.dcvar_model_fit" ] }, { "page": "compute_param_metrics", "title": "Compute scalar parameter recovery metrics", "topics": [ "compute_param_metrics" ] }, { "page": "compute_rho_metrics", "title": "Compute rho trajectory recovery metrics", "topics": [ "compute_rho_metrics" ] }, { "page": "covariate_effects", "title": "Extract covariate effect summaries", "topics": [ "covariate_effects", "covariate_effects.dcvar_covariate_fit", "covariate_effects.default" ] }, { "page": "dcvar", "title": "Fit the DC-VAR model", "topics": [ "dcvar" ] }, { "page": "dcvar_compare", "title": "Compare multiple fitted models using LOO-CV", "topics": [ "dcvar_compare" ] }, { "page": "dcvar_constant", "title": "Fit the constant copula model", "topics": [ "dcvar_constant" ] }, { "page": "dcvar_constant_fit-methods", "title": "S3 methods for dcvar_constant_fit objects", "topics": [ "coef.dcvar_constant_fit", "dcvar_constant_fit-methods", "plot.dcvar_constant_fit", "print.dcvar_constant_fit", "summary.dcvar_constant_fit" ] }, { "page": "dcvar_covariate", "title": "Fit the covariate DC-VAR model", "topics": [ "dcvar_covariate" ] }, { "page": "dcvar_covariate_fit-methods", "title": "S3 methods for covariate DC-VAR fits", "topics": [ "coef.dcvar_covariate_fit", "dcvar_covariate_fit-methods", "plot.dcvar_covariate_fit", "print.dcvar_covariate_fit", "summary.dcvar_covariate_fit" ] }, { "page": "dcvar_diagnostics", "title": "Extract MCMC diagnostics", "topics": [ "dcvar_diagnostics", "dcvar_diagnostics.dcvar_model_fit", "dcvar_diagnostics.default" ] }, { "page": "dcvar_fit-methods", "title": "S3 methods for dcvar_fit objects", "topics": [ "coef.dcvar_fit", "dcvar_fit-methods", "plot.dcvar_fit", "print.dcvar_fit", "summary.dcvar_fit" ] }, { "page": "dcvar_hmm", "title": "Fit the HMM copula model", "topics": [ "dcvar_hmm" ] }, { "page": "dcvar_hmm_fit-methods", "title": "S3 methods for dcvar_hmm_fit objects", "topics": [ "coef.dcvar_hmm_fit", "dcvar_hmm_fit-methods", "plot.dcvar_hmm_fit", "print.dcvar_hmm_fit", "summary.dcvar_hmm_fit" ] }, { "page": "dcvar_multilevel", "title": "Fit an experimental multilevel copula VAR(1) model", "topics": [ "dcvar_multilevel" ] }, { "page": "dcvar_multilevel_fit-methods", "title": "S3 methods for dcvar_multilevel_fit objects", "topics": [ "coef.dcvar_multilevel_fit", "dcvar_multilevel_fit-methods", "plot.dcvar_multilevel_fit", "print.dcvar_multilevel_fit", "summary.dcvar_multilevel_fit" ] }, { "page": "dcvar_sem", "title": "Fit an experimental SEM copula VAR(1) model", "topics": [ "dcvar_sem" ] }, { "page": "dcvar_sem_fit-methods", "title": "S3 methods for dcvar_sem_fit objects", "topics": [ "coef.dcvar_sem_fit", "dcvar_sem_fit-methods", "plot.dcvar_sem_fit", "print.dcvar_sem_fit", "summary.dcvar_sem_fit" ] }, { "page": "dcvar_stan_path", "title": "Get path to bundled Stan model file", "topics": [ "dcvar_stan_path" ] }, { "page": "dependence_summary", "title": "Extract a unified dependence summary", "topics": [ "dependence_summary", "dependence_summary.dcvar_constant_fit", "dependence_summary.dcvar_covariate_fit", "dependence_summary.dcvar_fit", "dependence_summary.dcvar_hmm_fit", "dependence_summary.dcvar_multilevel_fit", "dependence_summary.dcvar_sem_fit", "dependence_summary.default" ] }, { "page": "draws", "title": "Extract posterior draws", "topics": [ "draws", "draws.dcvar_model_fit", "draws.default" ] }, { "page": "fitted.dcvar_model_fit", "title": "Fitted values from a copula VAR model", "topics": [ "fitted.dcvar_model_fit", "fitted.dcvar_multilevel_fit", "fitted.dcvar_sem_fit" ] }, { "page": "hmm_states", "title": "Extract HMM state information", "topics": [ "hmm_states", "hmm_states.dcvar_hmm_fit", "hmm_states.default" ] }, { "page": "interpret_rho_trajectory", "title": "Interpret a rho trajectory in clinical terms", "topics": [ "interpret_rho_trajectory" ] }, { "page": "latent_states", "title": "Extract latent states from a SEM fit", "topics": [ "latent_states", "latent_states.dcvar_sem_fit", "latent_states.default" ] }, { "page": "loo.dcvar", "title": "Compute LOO-CV for a fitted model", "topics": [ "loo.dcvar", "loo.dcvar_constant_fit", "loo.dcvar_covariate_fit", "loo.dcvar_fit", "loo.dcvar_hmm_fit", "loo.dcvar_multilevel_fit", "loo.dcvar_sem_fit" ] }, { "page": "pit_test", "title": "KS test for PIT uniformity", "topics": [ "pit_test", "pit_test.dcvar_model_fit", "pit_test.default" ] }, { "page": "pit_values", "title": "Extract PIT values from a fitted model", "topics": [ "pit_values", "pit_values.dcvar_model_fit", "pit_values.default" ] }, { "page": "plot_diagnostics", "title": "Plot MCMC diagnostics", "topics": [ "plot_diagnostics" ] }, { "page": "plot_hmm_states", "title": "Plot HMM state posteriors", "topics": [ "plot_hmm_states" ] }, { "page": "plot_latent_states", "title": "Plot estimated latent states with credible intervals", "topics": [ "plot_latent_states" ] }, { "page": "plot_phi", "title": "Plot VAR(1) coefficient matrix as a heatmap", "topics": [ "plot_phi" ] }, { "page": "plot_pit", "title": "Plot PIT histograms", "topics": [ "plot_pit" ] }, { "page": "plot_ppc", "title": "Posterior predictive check for residual correlations", "topics": [ "plot_ppc" ] }, { "page": "plot_random_effects", "title": "Plot random effects (caterpillar plot)", "topics": [ "plot_random_effects" ] }, { "page": "plot_rho", "title": "Plot the rho trajectory with credible intervals", "topics": [ "plot_rho" ] }, { "page": "plot_trajectories", "title": "Plot and compare multiple rho trajectory shapes", "topics": [ "plot_trajectories" ] }, { "page": "predict.dcvar_model_fit", "title": "One-step-ahead predictions from a copula VAR model", "topics": [ "predict.dcvar_model_fit", "predict.dcvar_multilevel_fit", "predict.dcvar_sem_fit" ] }, { "page": "prepare_constant_data", "title": "Prepare data for the constant copula model", "topics": [ "prepare_constant_data" ] }, { "page": "prepare_dcvar_covariate_data", "title": "Prepare data for the covariate DC-VAR model", "topics": [ "prepare_dcvar_covariate_data" ] }, { "page": "prepare_dcvar_data", "title": "Prepare data for the DC-VAR model", "topics": [ "prepare_dcvar_data" ] }, { "page": "prepare_hmm_data", "title": "Prepare data for the HMM copula model", "topics": [ "prepare_hmm_data" ] }, { "page": "prepare_multilevel_data", "title": "Prepare data for the multilevel copula VAR model", "topics": [ "prepare_multilevel_data" ] }, { "page": "prepare_sem_data", "title": "Prepare data for the SEM copula VAR model", "topics": [ "prepare_sem_data" ] }, { "page": "print.dcvar_constant_summary", "title": "Print a dcvar_constant_summary object", "topics": [ "print.dcvar_constant_summary" ] }, { "page": "print.dcvar_covariate_summary", "title": "Print a dcvar_covariate_summary object", "topics": [ "print.dcvar_covariate_summary" ] }, { "page": "print.dcvar_hmm_summary", "title": "Print a dcvar_hmm_summary object", "topics": [ "print.dcvar_hmm_summary" ] }, { "page": "print.dcvar_multilevel_summary", "title": "Print a dcvar_multilevel_summary object", "topics": [ "print.dcvar_multilevel_summary" ] }, { "page": "print.dcvar_sem_summary", "title": "Print a dcvar_sem_summary object", "topics": [ "print.dcvar_sem_summary" ] }, { "page": "print.dcvar_summary", "title": "Print a dcvar_summary object", "topics": [ "print.dcvar_summary" ] }, { "page": "random_effects", "title": "Extract random effects from a multilevel fit", "topics": [ "random_effects", "random_effects.dcvar_multilevel_fit", "random_effects.default" ] }, { "page": "rho_constant", "title": "Generate a constant rho trajectory", "topics": [ "rho_constant" ] }, { "page": "rho_decreasing", "title": "Generate a logistically decreasing rho trajectory", "topics": [ "rho_decreasing" ] }, { "page": "rho_double_step", "title": "Generate a double-breakpoint (relapse pattern) rho trajectory", "topics": [ "rho_double_step" ] }, { "page": "rho_increasing", "title": "Generate a logistically increasing rho trajectory", "topics": [ "rho_increasing" ] }, { "page": "rho_random_walk", "title": "Generate a random walk rho trajectory on the Fisher-z scale", "topics": [ "rho_random_walk" ] }, { "page": "rho_scenario", "title": "Get a named trajectory scenario", "topics": [ "rho_scenario" ] }, { "page": "rho_step", "title": "Generate a single-breakpoint (step function) rho trajectory", "topics": [ "rho_step" ] }, { "page": "rho_trajectory", "title": "Extract the rho trajectory with credible intervals", "topics": [ "rho_trajectory", "rho_trajectory.dcvar_constant_fit", "rho_trajectory.dcvar_covariate_fit", "rho_trajectory.dcvar_fit", "rho_trajectory.dcvar_hmm_fit", "rho_trajectory.dcvar_multilevel_fit", "rho_trajectory.dcvar_sem_fit", "rho_trajectory.default" ] }, { "page": "simulate_breakpoint_data", "title": "Simulate data with a breakpoint rho trajectory", "topics": [ "simulate_breakpoint_data" ] }, { "page": "simulate_dcvar", "title": "Simulate data from a copula VAR(1) model", "topics": [ "simulate_dcvar" ] }, { "page": "simulate_dcvar_multilevel", "title": "Simulate data from a multilevel copula VAR(1) model", "topics": [ "simulate_dcvar_multilevel" ] }, { "page": "simulate_dcvar_sem", "title": "Simulate data from a SEM copula VAR(1) model", "topics": [ "simulate_dcvar_sem" ] }, { "page": "var_params", "title": "Extract VAR(1) parameter summaries", "topics": [ "var_params", "var_params.dcvar_model_fit", "var_params.dcvar_multilevel_fit", "var_params.dcvar_sem_fit", "var_params.default" ] } ], "_pkglogo": "https://github.com/benlug/dcvar/raw/HEAD/man/figures/logo.png", "_readme": "https://github.com/benlug/dcvar/raw/HEAD/README.md", "_rundeps": [ "abind", "backports", "bayesplot", "BH", "callr", "checkmate", "cli", "cpp11", "desc", "distributional", "dplyr", "farver", "generics", "ggplot2", "ggridges", "glue", "gridExtra", "gtable", "inline", "isoband", "labeling", "lifecycle", "loo", "magrittr", "matrixStats", "numDeriv", "patchwork", "pillar", "pkgbuild", "pkgconfig", "plyr", "posterior", "processx", "ps", "purrr", "QuickJSR", "R6", "RColorBrewer", "Rcpp", "RcppEigen", "RcppParallel", "reshape2", "rlang", "rstan", "S7", "scales", "StanHeaders", "stringi", "stringr", "tensorA", "tibble", "tidyr", "tidyselect", "utf8", "vctrs", "viridisLite", "withr" ], "_vignettes": [ { "source": "model-comparison.Rmd", "filename": "model-comparison.html", "title": "Comparing Copula VAR Models", "engine": "knitr::rmarkdown", "headings": [ "Overview", "Mathematical Background", "VAR(1) Marginals", "Gaussian Copula", "How the Models Differ", "Per-variable (mixed) margins", "Fitting All Three Models", "LOO-CV Comparison", "Extracting Tidy Summaries", "HMM-Specific Outputs", "Clinical Interpretation", "When to Use Which Model" ], "created": "2026-03-15 07:55:42", "modified": "2026-06-04 14:41:35", "commits": 6 }, { "source": "getting-started.Rmd", "filename": "getting-started.html", "title": "Getting Started with dcvar", "engine": "knitr::rmarkdown", "headings": [ "Installation", "Simulating Data", "Fitting the DC-VAR Model", "Inspecting Results", "Fitted Values and Predictions", "Tidy Parameter Summary", "Clinical Interpretation", "Visualisation", "LOO-CV Model Comparison" ], "created": "2026-03-15 07:55:42", "modified": "2026-04-26 14:31:44", "commits": 5 }, { "source": "simulation-tools.Rmd", "filename": "simulation-tools.html", "title": "Simulation Study Tools", "engine": "knitr::rmarkdown", "headings": [ "Trajectory Generators", "Visualising Trajectories", "Simulating Data", "Breakpoint Data Simulator", "Data Preparation", "Parameter Recovery Metrics", "Running a Mini Simulation Study" ], "created": "2026-03-15 07:55:42", "modified": "2026-04-22 12:20:38", "commits": 4 } ], "_score": 5.079181246047625, "_indexed": true, "_nocasepkg": "dcvar", "_universes": [ "benlug" ], "_previous": "0.3.0", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.3.1", "date": "2026-06-04T17:07:49.000Z", "distro": "noble", "commit": "28910395dbda7ad7ac94195d2d2efa4fa5e0ee41", "fileid": "b7a85513e87f2b2507bfad4b47855be3b10fbe5954a92f7debfc523d93c171f5", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/benlug/actions/runs/26966650463" }, { "r": "4.6.0", "os": "linux", "version": "0.3.1", "date": "2026-06-04T17:07:51.000Z", "distro": "noble", "commit": "28910395dbda7ad7ac94195d2d2efa4fa5e0ee41", "fileid": "e605804bbb9f1a9a95ddebacfaa1b0dfe66f1ea7866dad5856542b3cc0d78cb3", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/benlug/actions/runs/26966650463" }, { "r": "4.5.3", "os": "mac", "version": "0.3.1", "date": "2026-06-04T17:10:56.000Z", "commit": "28910395dbda7ad7ac94195d2d2efa4fa5e0ee41", "fileid": "c5ed9bb9195cf428d39142d03e002f9694ee40b4b79686df931cf6d92910dadf", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/benlug/actions/runs/26966650463" }, { "r": "4.6.0", "os": "mac", "version": "0.3.1", "date": "2026-06-04T17:10:39.000Z", "commit": "28910395dbda7ad7ac94195d2d2efa4fa5e0ee41", "fileid": "fd8e96b978695efba5eed5e098f84c28c935d94714a8153c91d6c42f6924c5c3", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/benlug/actions/runs/26966650463" }, { "r": "4.6.0", "os": "wasm", "version": "0.3.1", "date": "2026-06-04T17:08:20.000Z", "commit": "28910395dbda7ad7ac94195d2d2efa4fa5e0ee41", "fileid": "66619876413a589057c2c6b7f6cd85bf0f2422359bb8570502fd44369c407e0a", "status": "success", "buildurl": "https://github.com/r-universe/benlug/actions/runs/26966650463" }, { "r": "4.7.0", "os": "win", "version": "0.3.1", "date": "2026-06-04T17:04:57.000Z", "commit": "28910395dbda7ad7ac94195d2d2efa4fa5e0ee41", "fileid": "40fcbe061ba5a4400ce68739efc2f920449c8d7888943060d77cd39d53d06f2f", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/benlug/actions/runs/26966650463" }, { "r": "4.5.3", "os": "win", "version": "0.3.1", "date": "2026-06-04T17:04:45.000Z", "commit": "28910395dbda7ad7ac94195d2d2efa4fa5e0ee41", "fileid": "07c439ce47e47d9ce746992ef362b58320eff103382930827d2f216bac229d4a", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/benlug/actions/runs/26966650463" }, { "r": "4.6.0", "os": "win", "version": "0.3.1", "date": "2026-06-04T17:04:56.000Z", "commit": "28910395dbda7ad7ac94195d2d2efa4fa5e0ee41", "fileid": "6fce9aee9769d6ab1e975c151be0db8f1f8382046cdc095b5482de8e8f816a5d", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/benlug/actions/runs/26966650463" } ] }